Update Efficient Frontier with Sharpe Ratio.py

Map Symbol+Weight portfolio keys to the correct array of stock weights. `selected` does not have the same order as that used in the pandas dataframe
https://medium.com/@troy.engelhardt/hey-just-letting-you-know-that-your-final-data-frame-labelled-df-is-in-fact-mislabelled-6861298efcda#--responses

Author: Jesse Osiecki

Tutorials/Efficient Frontier with Sharpe Ratio.py

@@ -55,7 +55,7 @@
              'Sharpe Ratio': sharpe_ratio}
 
 # extend original dictionary to accomodate each ticker and weight in the portfolio
-for counter,symbol in enumerate(selected):
+for counter,symbol in enumerate(cov_annual.columns):
     portfolio[symbol+' Weight'] = [Weight[counter] for Weight in stock_weights]
 
 # make a nice dataframe of the extended dictionary
@@ -74,4 +74,4 @@
 plt.xlabel('Volatility (Std. Deviation)')
 plt.ylabel('Expected Returns')
 plt.title('Efficient Frontier')
-plt.show()
+plt.show()